Mass spectrometry imaging of glycans from tissue sections and improved analyte detection methods

ABSTRACT

The presently disclosed subject matter provides methods using mass spectrometry for direct profiling of N-linked glycans from a biological sample. In addition, the embodiments of the present invention also disclose novel methods, known as targeted analyte detection (TAD), for improving the detection limit of MALDI-MS. These methods take advantage of the carrier effect of the added standard analytes, which occurs due to the generic sigmoidal shape of the calibration curve. The functionality of TAD depends on the relative enhancement of sensitivity over the increase of the standard deviation at the analysis of target analytes with spiking in exogenous concentration. At certain ranges of exogenous concentration, the increment in the sensitivity overcomes the standard deviation, resulting in an improved LOD. Theoretically, exogenous concentrations approximately at 1 LODorig would generate the optimum LOD improvement. TAD is a cost-effective LOD improvement method, which is not limited to a certain group of analytes, or detection methods or instruments. It can be applied to enhance the detection of any analyte with different detection methods, provided that the analyte of interest can be extracted or is available in synthetic form.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.14/402,478, filed Nov. 20, 2014, which is 35 U.S.C. § 371 U.S. nationalentry of International Application PCT/US2013/042408, having aninternational filing date of May 23, 2013, which claims the benefit ofU.S. Provisional Application No. 61/650,646, filed on May 23, 2012, and61/681,417, filed on Aug. 9, 2012, and 61/776,534, filed Mar. 11, 2013,each of which are hereby incorporated by reference for all purposes asif fully set forth herein.

FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

This invention was made with government support under U01CA152813awarded by the National Institutes of Health (NIH). The government hascertain rights in the invention.

BACKGROUND OF THE INVENTION

Glycans play multi-faceted roles in many biological processes andaberrant glycosylation is associated with most of the diseases thataffect mankind. Glycans are post-translation modifications of proteinsthat are involved in cell growth, cytokinesis, differentiation,transcription regulation, signal transduction, ligand-receptor binding,interactions of cells with other cells and extracellular matrix (ECM)and bacterial and viral infection, among other functions (see FIG. 1).Glycan misregulations and structural changes occur in most of thediseases that affect the human.

Lectin histochemistry methods are commonly used to stain tissue glycanson formalin-fixed paraffin-embedded (FFPE) sections (see FIG. 2). Somelectins have high affinities for the epitopes of certain glycans. Forexample, Concanavilin A (ConA) can be used as a ligand for high-mannoseglycans, Sambucus nigra agglutinin (SNA) for sialylated glycans, andAlueria aurantia lectin (AAL) for fucosylated structures. Despite theimpact the lectin chemistry has had on the field, it has limitations.For example, lectins provide minimal structural information about thestained epitopes, they are limited to one epitope at a time on eachtissue section, they are quantitative and, compared with antibodies,have lower affinities for the glycans. Further, very few monoclonalantibodies have been developed for glycans.

Matrix-assisted laser desorption-ionization time-of-flight massspectrometry (MALDI-TOF MS) serves as a major technique for fast andaccurate analysis of a number of molecules from complex mixtures such ascells, tissues and serum samples. Although MALDI-TOF MS has beensuccessfully applied for detection, identification and validation ofmany peptides and molecules, it has proven ineffective for analyzing lowabundance molecules from complex mixtures. Considering the extremelywide range of protein concentrations in plasma (i.e. from albumin at10¹⁰ pg/mL to interleukins at 10 pg/mL), the lower-abundant proteins orpeptides are dominated by the abundant serum contents and fail to bedetected in a mixture. In addition, background and chemical noise(coming from desorbed matrix cluster) interfere with the MS signal andfurther compromise the sensitivity and detectability for low-abundanceanalytes. Despite the technological advances in MALDI-TOFinstrumentation, the suboptimal transmission efficiency of the massanalyzer, and detection efficiency of the detector, also result in someloss of analyte, which is another factor that reduces the detectionlimit and sensitivity of MALDI-TOF MS with low-abundant analytes. On theother hand, the concentration of potential disease biomarkers, such asglycans lies in the lower range of concentrations in serum, particularlyat the early stages of the disease where screening is crucial.

Therefore, there still exists a need to improve methods for generatingstructural information of glycans in FFPE sections, as well as the needto improve the sensitivity and detection limits of MALDI-TOF MSanalytical methods for glycans, peptides and other target analytes, inorder to be effective for biomarker discovery research.

SUMMARY OF THE INVENTION

In accordance with an embodiment, the present invention provides amethod for direct profiling of N-linked glycans in a biological sample,the method comprising: (a) obtaining a biological sample comprising atleast one glycoprotein; (b) denaturing the at least one glycoprotein inthe biological sample; (c) releasing at least one glycan from the atleast one glycoprotein; (d) coating the biological sample with a matrix;(e) analyzing the at least one glycan using mass spectrometry; andwherein spatial distribution of the at least one glycan is maintained.

In accordance with another embodiment, the present invention provides amethod for diagnosing a disease or condition in a subject, the methodcomprising: (a) comparing the N-linked glycan profile from a subject toan N-linked glycan profile from a normal sample or diseased sample; and(b) determining whether the subject has the disease or condition;wherein the glycan profile is determined by: (i) obtaining a biologicalsample comprising at least one glycoprotein; (ii) denaturing the atleast one glycoprotein in the biological sample; (iii) releasing atleast one glycan from the at least one glycoprotein; (iv) coating thebiological sample with a matrix; (v) analyzing the at least one glycanusing mass spectrometry; and wherein spatial distribution of the atleast one glycan is maintained.

In accordance with still another embodiment, the present inventionprovide a method for improving the limit of detection of one or moretarget analytes in a sample, the method comprising: a) obtaining asample; b) adding to the sample a known concentration of one or moretarget analytes; c) applying the sample to a matrix; d) analyzing the atleast one target analyte using mass spectrometry wherein the limit ofdetection of the one or more target analytes is calculated using theformula Signal (C+LOD_(c))=Signal (C)+3SD_(c).

In accordance with yet another embodiment, the present invention providea method for preserving and detecting sialic acid residues in a samplecomprising: (a) obtaining a biological sample comprising at least onesialic acid containing glycoprotein; (b) adding p-toluidine to thesample; (c) denaturing the at least one sialic acid containingglycoprotein in the biological sample; (d) releasing at least one sialicacid containing glycan from the at least one sialic acid containingglycoprotein; (e) coating the biological sample with a matrix; (f)analyzing the at least one sialic acid containing glycan using massspectrometry; and wherein spatial distribution of the at least onesialic acid containing glycan is maintained.

Certain aspects of the presently disclosed subject matter having beenstated hereinabove, which are addressed in whole or in part by thepresently disclosed subject matter, other aspects will become evident asthe description proceeds when taken in connection with the accompanyingExamples and Figures as best described herein below.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows that glycans play multi-faceted roles in many biologicalprocesses.

FIG. 2 shows the glycan imaging methods known in the art for FFPE tissuesections (Prior Art).

FIG. 3 shows mass spectrometry imaging of N-linked glycans on FFPEtissue sections.

FIG. 4 shows coronal mouse brain tissue sections are imaged with andwithout PNGase F printing. PNGase F releases the N-linked glycans fromFFPE sections for MALDI-MS imaging (the brain stem comprises theinterbrain, midbrain, and hindbrain; mostly the midbrain is shown inthis figure).

FIG. 5 shows ion images of fucosylated glycans on mouse brain coronalsections (CNU: cerebral nuclei; CTX: cerebral cortex; BS: brain stem).

FIG. 6 shows glycans detected from PNGase F-printed mouse brain tissuesection using MALDI-MS.

FIG. 7 shows that labeling the sialylated N-glycans with P-toluidineprotects them in MALD-MS.

FIG. 8 shows that in situ P-toluidine labeling of sialylated glycans onFFPE tissues improves detection.

FIG. 9 shows imaging of sialylated N-linked glycans on prostate tissuesections.

FIG. 10 shows MALDI-MS imaging to directly profile and image linkedglycans from FFPE tissue sections (top) and in situ chemical labeling oftissue sections to image FFPE tissue sections (bottom).

FIG. 11 depicts presence of background, limited dynamic range, limit ofdetection, limited detection efficiency and variations cause thedeviation between the realistic calibration curve from the ideal curvewhere the signal is proportional to the analyte concentration. Shiftingthe reference point to the linear dynamic range of the calibration curvewill enhance the sensitivity and improve the LOD by spiking in certainexogenous concentrations of target analyte. The original calibrationcurve of the analyte of interest is used for this estimation of thepredicted LODC. The reference point for calculation of LODC is shiftedto the given exogenous concentration.

FIG. 12 shows the correlation between the LOD, sensitivity and thestandard deviation is depicted. The slope of the dotted line is bydefinition the average sensitivity over the concentration range from 0to LOD. On the other hand, this slope equals three times the standarddeviation divided by LOD. Therefore, LOD is proportional to the SDdivided by the sensitivity.

FIG. 13A-13D shows how sensitivity and standard deviation of themeasurements change with the analyte concentration. A) Calibration curvefor Angiotensin II generated using Applied Biosystems 4800 MALDI-TOF/TOFanalyzer is depicted. B) Sensitivity sharply rises as the concentrationincreases to supra-LOD levels. C) The variation in standard deviation atlow concentrations is modest compared to increments in the sensitivity.D) Coefficient of variation (CV) rapidly decreases from 40% at thebackground to ˜5% for higher end of the curve. The LOD is marked by thevertical dashed line.

FIG. 14A-14B depicts the mass spectral peak of Angiotensin I(ma=1296.685) at the reference point of LOD measurement (dotted line)and endogenous concentration X=31.25 fmol/μL (solid line) for A) controlgroup, where C=0 and LOD_(orig)=64.5 fmol/μL and B) TAD experiment whereC=50 fmol/μL and LOD_(C)=22.5 fmol/μL. A) In the control group, thesolid line is hardly differentiated from the background. B) However,improving the LOD in the TAD experiment leads to significant distinctionof the signal from the background at concentration X=31.25 fmol/μL. Thepeak intensities were normalized to the heavy isotope-peptide.

FIG. 15A-15B shows experimental improvement factors for three peptidesin simple background are averaged over four replicates. A) When usingα-cyano-4-hydroxycinnamic acid (CHCA), the LOD is improved in all of the9 experimental pairs yielding improvement factors greater than 1. B) TheLOD is improved in 8 of the 9 experimental pairs when2,5-dihydroxybenzoic acid (DHB) is used as the MALDI matrix. The dottedline shows the threshold of LOD improvement. The error-bars show thestandard error of the mean.

FIG. 16A-16B depicts an example of the predicted improvement factor forAngiotensin II in the simple background experiment using A) CHCA and B)DHB is shown. The highest improvement factor is achieved at exogenousconcentrations close to the LOD_(orig) of the target peptide for bothCHCA (0.67 LOD_(orig)) and DHB (1.46 LOD_(orig)) matrices. Due to theincrease in the standard deviation of the measurements, the improvementfactor decreases at higher exogenous concentrations.

FIG. 17 shows experimental LOD improvement factors for three peptides incomplex background using CHCA as the matrix are averaged over triplicateexperiments. In 10 out of the 15 experiments, the LOD is improved. Theimprovement factors depend on the concentration of the exogenous analytespiked into the sample as well as the analyte of interest. Theerror-bars depict the standard error of the mean.

FIG. 18 depicts an example of predicted improvement factor forAngiotensin II in the complex background experiment. The highesttheoretical improvement factor is achieved at exogenous concentrationsclose to the LOD_(orig) of that peptide, similar to the simplebackground experiment. The curve is bell-shaped yielding an improvementfactor close to 1 at lower concentrations, and decreasing at higherconcentrations.

DETAILED DESCRIPTION OF THE INVENTION

Methods are provided herein which are directed to improved methods ofanalyzing various target analytes including, for example, proteins,peptides and carbohydrates. As used herein, the term “carbohydrate” isintended to include any of a class of aldehyde or ketone derivatives ofpolyhydric alcohols. Therefore, carbohydrates include starches,celluloses, gums and saccharides. Although, for illustration, the term“saccharide” or “glycan” is used below, this is not intended to belimiting. It is intended that the methods provided herein can bedirected to any carbohydrate, and the use of a specific carbohydrate isnot meant to be limiting to that carbohydrate only.

The terms “sample,” “patient sample,” “biological sample,” and the like,encompass a variety of sample types obtained from a patient, individual,or subject and can be used in a diagnostic, prognostic or monitoringassay. The patient sample may be obtained from a healthy subject, adiseased patient including, for example, a patient having associatedsymptoms of SWS, KTWS or PWS. Moreover, a sample obtained from a patientcan be divided and only a portion may be used for diagnosis, prognosisor monitoring. Further, the sample, or a portion thereof, can be storedunder conditions to maintain sample for later analysis. The definitionspecifically encompasses blood and other liquid samples of biologicalorigin (including, but not limited to, peripheral blood, serum, plasma,urine, saliva, amniotic fluid, stool and synovial fluid), solid tissuesamples such as a biopsy specimen or tissue cultures or cells derivedtherefrom and the progeny thereof. In a specific embodiment, a samplecomprises a skin sample. In another embodiment, a sample of brain tissueis used. In other embodiments, a sample comprises a blood or serumsample. The definition also includes samples that have been manipulatedin any way after their procurement, such as by centrifugation,filtration, precipitation, dialysis, chromatography, treatment withreagents, washed, or enriched for certain cell populations. The termsfurther encompass a clinical sample, and also include cells in culture,cell supernatants, tissue samples, organs, and the like. Samples mayalso comprise fresh-frozen and/or formalin-fixed, paraffin-embeddedtissue blocks, such as blocks prepared from clinical or pathologicalbiopsies, prepared for pathological analysis or study byimmunohistochemistry.

The terms “providing a sample” and “obtaining a biological (or patient)sample” are used interchangeably and mean to provide or obtain abiological sample for use in methods described in this invention. Mostoften, this will be done by removing a sample of cells from a patient,but can also be accomplished by using previously isolated cells (e.g.,isolated by another person, at another time, and/or for anotherpurpose), or by performing the methods of the invention in vivo.Archival tissues, having treatment or outcome history, can also be used.

The terms “polypeptide,” “peptide” and “protein” are usedinterchangeably herein to refer to a polymer of amino acid residues. Theterms apply to amino acid polymers in which one or more amino acidresidue is an artificial chemical mimetic of a corresponding naturallyoccurring amino acid, as well as to naturally occurring amino acidpolymers, those containing modified residues, and non-naturallyoccurring amino acid polymer.

The term “amino acid” refers to naturally occurring and synthetic aminoacids, as well as amino acid analogs and amino acid mimetics thatfunction similarly to the naturally occurring amino acids. Naturallyoccurring amino acids are those encoded by the genetic code, as well asthose amino acids that are later modified, e.g., hydroxyproline,.gamma.-carboxyglutamate, and O-phosphoserine. Amino acid analogs refersto compounds that have the same basic chemical structure as a naturallyoccurring amino acid, e.g., an .alpha. carbon that is bound to ahydrogen, a carboxyl group, an amino group, and an R group, e.g.,homoserine, norleucine, methionine sulfoxide, methionine methylsulfonium. Such analogs may have modified R groups (e.g., norleucine) ormodified peptide backbones, but retain the same basic chemical structureas a naturally occurring amino acid. Amino acid mimetics refers tochemical compounds that have a structure that is different from thegeneral chemical structure of an amino acid, but that functionssimilarly to a naturally occurring amino acid.

Amino acids may be referred to herein by either their commonly knownthree letter symbols or by the one-letter symbols recommended by theIUPAC-IUB Biochemical Nomenclature Commission. Nucleotides, likewise,may be referred to by their commonly accepted single-letter codes.

“Conservatively modified variants” applies to both amino acid andnucleic acid sequences. With respect to particular nucleic acidsequences, conservatively modified variants refers to those nucleicacids which encode identical or essentially identical amino acidsequences, or where the nucleic acid does not encode an amino acidsequence, to essentially identical or associated, e.g., naturallycontiguous, sequences. Because of the degeneracy of the genetic code, alarge number of functionally identical nucleic acids encode mostproteins. For instance, the codons GCA, GCC, GCG and GCU all encode theamino acid alanine. Thus, at every position where an alanine isspecified by a codon, the codon can be altered to another of thecorresponding codons described without altering the encoded polypeptide.Such nucleic acid variations are “silent variations,” which are onespecies of conservatively modified variations. Every nucleic acidsequence herein which encodes a polypeptide also describes silentvariations of the nucleic acid. One of skill will recognize that incertain contexts each codon in a nucleic acid (except AUG, which isordinarily the only codon for methionine, and TGG, which is ordinarilythe only codon for tryptophan) can be modified to yield a functionallyidentical molecule. Accordingly, often silent variations of a nucleicacid which encodes a polypeptide is implicit in a described sequencewith respect to the expression product, but not with respect to actualprobe sequences.

As to amino acid sequences, one of ordinary skill in the art recognizesthat individual substitutions, deletions or additions to a nucleic acid,peptide, polypeptide, or protein sequence which alters, adds or deletesa single amino acid or a small percentage of amino acids in the encodedsequence is a “conservatively modified variant” where the alterationresults in the substitution of an amino acid with a chemically similaramino acid. Conservative substitution tables providing functionallysimilar amino acids are well known in the art. Such conservativelymodified variants are in addition to and do not exclude polymorphicvariants, interspecies homologs, and alleles of the invention. Typicalconservative substitutions for one another: 1) Alanine (A), Glycine (G);2) Aspartic acid (D), Glutamic acid (E); 3) Asparagine (N), Glutamine(Q); 4) Arginine (R), Lysine (K); 5) Isoleucine (I), Leucine (L),Methionine (M), Valine (V); 6) Phenylalanine (F), Tyrosine (Y),Tryptophan (W); 7) Serine (S), Threonine (T); and 8) Cysteine (C),Methionine (M) (see, e.g., Creighton, Proteins (1984)).

As used herein, the term “saccharide” refers to a polymer comprising oneor more monosaccharide groups. Saccharides, therefore, include mono-,di-, tri- and polysaccharides (or glycans). Glycans can be branched orbranched. Glycans can be found covalently linked to non-saccharidemoieties, such as lipids or proteins (as a glycoconjugate). Thesecovalent conjugates include glycoproteins, glycopeptides,peptidoglycans, proteoglycans, glycolipids and lipopolysaccharides. Theuse of any one of these terms also is not intended to be limiting as thedescription is provided for illustrative purposes. In addition to theglycans being found as part of a glycoconjugate, the glycans can also bein free form (i.e., separate from and not associated with anothermoiety). The use of the term peptide is not intended to be limiting. Themethods provided herein are also intended to include proteins where“peptide” is recited.

In some embodiments, the methods are methods of diagnosis and thepattern is associated with a diseased state. In one preferredembodiment, the pattern associated with a diseased state is a patternassociated with cancer, such as prostate cancer, melanoma, bladdercancer, breast cancer, lymphoma, ovarian cancer, lung cancer, colorectalcancer or head and neck cancer. In other preferred embodiments, thepattern associated with a diseased state is a pattern associated with animmunological disorder; a neurodegenerative disease, such as atransmissible spongiform encephalopathy, Alzheimer's disease orneuropathy; inflammation; rheumatoid arthritis; cystic fibrosis; or aninfection, preferably viral or bacterial infection. In otherembodiments, the method is a method of monitoring prognosis and theknown pattern is associated with the prognosis of a disease. In yetanother embodiment, the method is a method of monitoring drug treatmentand the known pattern is associated with the drug treatment. Inparticular, the methods (e.g., analysis of glycome profiles) are usedfor the selection of population-oriented drug treatments and/or inprospective studies for selection of dosing, for activity monitoringand/or for determining efficacy endpoints.

Methods of analyzing glycans of glycoconjugates can also includecleaving the glycans from glycoconjugates using a releasing agent. Areleasing agent can comprise any chemical or enzymatic methods orcombinations thereof that are known in the art. An example of a chemicalmethod for cleaving glycans from glycoconjugates is hydrazinolysis oralkali borohydrate. Enyzmatic methods include methods that are specificto N- or O-linked sugars. These enzymatic methods include the use ofEndoglycosidase H (Endo H), Endoglycosidase F (EndoF), N-Glycanase F(PNGaseF) or combinations thereof. In some preferred embodiments,PNGaseF is used when the release of N-glycans is desired. When PNGaseFis used for glycan release the proteins is, for example, first unfoldedprior to the use of the enzyme. The unfolding of the protein can beaccomplished with any of the denaturing agents provided above.

Mass spectrometry imaging (MSI) is a powerful tool that has been used tocorrelate various peptides, proteins, lipids and metabolites with theirunderlying histopathology in tissue sections. Taking advantage of therapid advances in mass spectrometry, MSI can push the limits ofglycomics studies. Mass spectrometry imaging offers some advantages overthe conventional methods that support its use as a complementarytechnique to lectin histochemistry. One significant advantage is thatMALDI imaging combined with tandem mass spectrometry reveals detailedstructural information about the glycans in a sample. A wide range ofmolecular weights can be detected by mass spectrometry imaging. Also,the high mass resolution allows distinguishing two peaks with closemolecular weights, which subsequently improves the detectionspecificity. In addition, tens or even hundreds of glycans can bedetected at femtomole levels in one single image, allowing detection oflow concentrations of molecules. Therefore, MALDI imaging facilitateshigh-throughput analysis of tissue glycans. MALDI imaging can also beused for performing quantitative assays. Another significant advantageof MALDI imaging is that it has the capability of detecting an unknowncompound without any a priori knowledge of the analytes. Therefore, thistechnique is particularly suitable for biomarker discovery research.

Matrix-assisted laser desorption/ionization (MALDI) is a soft ionizationmass spectrometric technique that is suitable for use in the analysis ofbiomolecules, such as proteins, peptides, sugars, and the like, whichtend to be fragile and fragment when ionized by conventional ionizationmethods.

Generally, MALDI comprises a two-step process. In the first step,desorption is triggered by an ultraviolet (UV) laser beam. The matrixmaterial absorbs the UV laser radiation, which leads to the ablation ofan upper layer of the matrix material, thereby producing a hot plume.The hot plume contains many species: neutral and ionized matrixmolecules, protonated and deprotonated matrix molecules, matrixclusters, and nanodroplets. In the second step, the analyte moleculesare ionized, e.g., protonated or deprotonated, in the hot plume.

The matrix material comprises a crystallized molecule capable ofabsorbing the UV laser radiation. Common matrix materials include, butare not limited to, 3,5-dimethoxy-4-hydroxycinnamic acid (sinapinicacid), CHCA, and DHB. A solution of the matrix material is made, eitherin highly purified water and an organic solvent, such as acetonitrile orethanol. In some embodiments, a small amount of trifluoroacetic acid(TFA) also can be added to the solution.

The matrix solution can then be mixed with the analyte, e.g., a proteinsample. This solution is then deposited onto a MALDI plate, wherein thesolvents vaporize leaving only the recrystallized matrix comprising theanalyte molecules embedded in the MALDI crystals.

The type of mass spectrometer typically used with MALDI is thetime-of-flight (TOF) mass spectrometer, which has a large mass range. Inaccordance with one or more embodiments of the present invention, themass spectrometric method comprises MALDI-TOF. In particularembodiments, the mass spectrometric method comprises MALDI-TOF tandemmass spectrometry. In yet another embodiment, mass spectrometry can becombined with another appropriate method(s) as may be contemplated byone of ordinary skill in the art, for example, HPLC, or LC/MS and thelike.

In accordance with one or more embodiments of the present invention, themass spectrometry comprises a MALDI-quadrupole ion trap (QIT)-TOF massspectrometer, which, in some embodiments, can include a tandem massspectrometer system. Such mass spectrometer systems provide for thestructural characterization of biomolecules, not only their massmeasurement. Such systems provide multiple advantages for characterizingbiomolecules including, but not limited to, time of flight resolutionand accuracy independent of laser energy applied and a wide mass rangeof ions trapped (up to 20 kDa). Such systems can comprise a MALDI plate,an ion trap, a reflection and a detector.

In accordance with an embodiment, the present invention provides a MSItechnique that has been developed for direct profiling of N-linkedglycans from formalin-fixed paraffin-embedded (FFPE) tissues. FFPEtissues are sectioned on indium tin oxide coated glass slides formatrix-assisted laser desorption/ionization mass spectrometry(MALDI-MS). Deparaffinization and rehydration of the tissue sections arefollowed by antigen retrieval and denaturing of the proteins. Areleasing agent, such as Peptide-N-Glycosidase F (PNGase F), can besprayed over the tissue sections to release the N-linked glycans fromthe proteins, while preserving their spatial distribution. Samples canthen be spray-coated with matrix and analyzed by MALDI-MS-MS2-MSn(Shimadzu Axima Resonance in positive mode).

In accordance with another embodiment, the present invention provides amethod for direct profiling of N-linked glycans in a biological sample,the method comprising: (a) obtaining a biological sample comprising atleast one glycoprotein; (b) denaturing the at least one glycoprotein inthe biological sample; (c) releasing at least one glycan from the atleast one glycoprotein; (d) coating the biological sample with matrix;and (e) analyzing the at least one glycan using mass spectrometry; andwherein spatial distribution of the at least one glycan is maintained.

In some embodiments, the biological sample is a paraffin-embedded tissueand/or formalin-fixed tissue. In still another embodiment, thebiological sample is rehydrated. In a further embodiment, the biologicalsample is deposited on a solid support.

It will be understood by those of skill in the art that for spatialdistribution of the glycans in the biological sample to be maintained, asolid support, such as a glass plate or slide, or similar support, canbe used with sectioning. In some embodiments, a biological sample, suchas a tissue, is raster scanned by a laser in the x and y directions andmass spectra are acquired for each pixel on the tissue.

In accordance with another embodiment, the denaturation of theglycoprotein(s) occurs by heating the biological sample and/orincubating the biological sample with a proteolytic enzyme for asufficient period of time.

In accordance with still another embodiment, releasing the N-linkedglycan(s) on the glycoprotein(s) occurs by using a releasing agent, forexample, Peptide-N-Glycosidase F (PNGase F). In further embodiments,releasing the glycan(s) occurs by using a microarray printer incombination with a releasing agent.

In still further embodiments, a matrix is used, such as2,5-dihydroxybenzoic acid (DHB). In particular embodiments, the massspectrometry method used is MALDI-mass spectrometry.

In accordance with an embodiment, the present invention also provides ageneric technique for improving the sensitivity and detection limit ofMALDI-MS. This method, named targeted analyte detection (TAD),selectively enhances the detection of analytes (target molecules) ofinterest, such as proteins, peptides, and glycans, for example. In TAD,a small known amount of analyte of interest is spiked into the sample,thereby elevating the concentration to levels above the noise, where theinterference of the noise is relatively reduced and the sensitivity isincreased. The added analyte acts as a carrier to suppress the matrixeffect (introduced by interferences with other compounds in the sample)and enhances ion abundance of analyte of interest. The measured signalis thus contributed by both the endogenous and exogenous (spiked-in)analytes. Therefore, TAD uses the added standard to reveal theendogenous target analyte that was otherwise buried in the noise.

As disclosed herein, the feasibility of TAD in improving the detectionlimit of MALDI-MS is presented. Additionally, the present invention alsoprovides a systematic method for optimizing the spiking amount needed toachieve the maximum improvement in the limit of detection (LOD). Themain advantage of TAD is that it is not limited to certain types ofanalytes, provided that the analyte of interest is available or can besynthesized for spiking into the unknown sample. Furthermore, thisapproach takes advantage of the generic sigmoidal shape of thecalibration curve, which is very reproducible in a wide range ofanalytical instruments. Therefore, this method might be capable ofimproving the sensitivity in a wide range of instruments regardless ofthe detection technologies, including but not limited to massspectrometers.

Estimation of LOD.

A code was developed to estimate the predicted LOD. The mean andstandard deviation of the measurements for the control group without TADsolution was used as the input to the code. For each target analyte, theoriginal LOD was calculated based on the commonly used definition of LODas shown in eq 1:Signal(LOD_(orig))=Signal(Background)+3SD,  (1)where LOD_(orig) is the limit of detection in the absence of anyexogenous target analyte and Signal (LOD_(orig)) is the total signal atthis concentration. Signal (Background) represents the background signalmean and SD denotes the background signal standard deviation (FIG. 11).

For a given exogenous concentration of the target peptide in TADsolution, the LOD was estimated by shifting the reference point of thebackground to the given exogenous spiking peptide concentration (C) usedin TAD solution. The signal and standard deviation at any concentrationwere estimated by interpolating the signal and standard deviation of thecalibration curve without exogenous peptide in TAD solution,respectively. Denote the limit of detection at the spiking concentrationC fmol/μL of the target analyte in the TAD solution, as LOD_(C) andLOD_(C) should then satisfy eq 2:Signal(C+LOD_(C))=Signal(C)+3SD_(C).  (2)

It is noted that for the control set with no spiking target peptide inthe TAD solution, C is set to zero (FIG. 1 and eq 1).

Ideally, the measured signal for each analyte is proportional to theamount of that analyte in the sample. However, the detection accuracy iscompromised by factors such as background, detection efficiency, samplepreparation and signal detection variations, and the limit of detectionin mass spectrometry. Presence of background results in a nonzero signaleven at zero concentration of the analyte. Suboptimal detectionefficiency compromises the output signal. Analyte concentrationvariations introduced by analyte-matrix cocrystallization,desorption/ionization, analyzer and detector add noise to themeasurements, thus limiting the threshold as well as the confidence oflow abundance analyte detection.

Therefore, in accordance with some embodiments, the practicalcalibration curve of MALDI-MS, which is the measured mass spectralsignal versus a given analyte concentration, differs from the idealcurve in crucial aspects (FIG. 11). The sigmoidal shape of the practicalcalibration curve arises from these differences, whereas the signalintensity is linearly proportional to the analyte concentration in theideal curve. LOD corresponds to the concentration of an analyte thatproduces a signal at least as large as the background mean plus threetimes the background standard deviation. Thus, the LOD can be estimatedby the standard deviation of the background as well as the sensitivity,based on eq 3 (FIG. 12):LOD=3SD/Sensitivity,  (3)where sensitivity is defined as the slope of the calibration curve. Eq 3indicates that LOD is directly proportional to the standard deviationand inversely proportional to the sensitivity; therefore, lower noiselevel and higher sensitivity improve the LOD. This provides theopportunity that one can improve the LOD by improving thereproducibility or sensitivity.

In accordance with one or more embodiments, the methods of the presentinvention allow direct imaging of glycans on tissues to determinedisease-specific glycosylation changes. Therefore, in some embodiments,these methods provide a method of diagnosing a disease or condition in asubject comprising: (a) comparing the N-linked glycan profile from asubject to an N-linked glycan profile from a normal sample or diseasedsample; (b) determining whether the subject has the disease orcondition; and wherein the glycan profile is determined using thepresently disclosed methods. In other embodiments, the disease ordisorder is a cancer.

It will be understood by those of ordinary skill in the art that otherdiseases or conditions in which aberrant glycoproteins are indicativecan be identified using the inventive methods provided herein.

In accordance with one or more embodiments, the presently disclosedmethods detect glycoproteins, glycoprotein biomarkers, and/or aberrantglycans by tissue glycan imaging. In other embodiments, therapeutictargets can be identified by the presently disclosed methods byidentifying aberrant glycans.

In further embodiments, diagnostic kits comprising instructions andmaterials that can be used to perform the presently disclosed methodsalso are provided.

As stated above, the glycosylation of a protein may be indicative of anormal or a disease state. Therefore, methods are provided fordiagnostic purposes based on the analysis of the glycosylation of aprotein or set of proteins, such as the total glycome. The methodsprovided herein can be used for the diagnosis of any disease orcondition that is caused or results in changes in a particular proteinglycosylation or pattern of glycosylation. These patterns can then becompared to “normal” and/or “diseased” patterns to develop a diagnosis,and treatment for a subject. For example, the methods provided can beused in the diagnosis of cancer, inflammatory disease, benign prostatichyperplasia (BPH), etc.

The diagnosis can be carried out in a person with or thought to have adisease or condition. The diagnosis can also be carried out in a personthought to be at risk for a disease or condition. “A person at risk” isone that has either a genetic predisposition to have the disease orcondition or is one that has been exposed to a factor that couldincrease his/her risk of developing the disease or condition.

Detection of cancers at an early stage is crucial for its efficienttreatment. Despite advances in diagnostic technologies, many cases ofcancer are not diagnosed and treated until the malignant cells haveinvaded the surrounding tissue or metastasized throughout the body.Although current diagnostic approaches have significantly contributed tothe detection of cancer, they still present problems in sensitivity andspecificity.

In accordance with one or more embodiments of the present invention, itwill be understood that the types of cancer diagnosis which may be made,using the methods provided herein, is not necessarily limited. Forpurposes herein, the cancer can be any cancer. As used herein, the term“cancer” is meant any malignant growth or tumor caused by abnormal anduncontrolled cell division that may spread to other parts of the bodythrough the lymphatic system or the blood stream.

The cancer can be a metastatic cancer or a non-metastatic (e.g.,localized) cancer. As used herein, the term “metastatic cancer” refersto a cancer in which cells of the cancer have metastasized, e.g., thecancer is characterized by metastasis of a cancer cells. The metastasiscan be regional metastasis or distant metastasis, as described herein.

The terms “treat,” and “prevent” as well as words stemming therefrom, asused herein, do not necessarily imply 100% or complete treatment orprevention. Rather, there are varying degrees of treatment or preventionof which one of ordinary skill in the art recognizes as having apotential benefit or therapeutic effect. In this respect, the inventivemethods can provide any amount of any level of diagnosis, staging,screening, or other patient management, including treatment orprevention of cancer in a mammal. Furthermore, the treatment orprevention provided by the inventive method can include treatment orprevention of one or more conditions or symptoms of the disease, e.g.,cancer, being treated or prevented. Also, for purposes herein,“prevention” can encompass delaying the onset of the disease, or asymptom or condition thereof.

In accordance with an embodiment, the present invention provides a useof a glycan profile prepared using the method disclosed herein todiagnose a disease or condition in a subject, comprising comparing theglycan profile from a subject to a glycan profile from a normal sample,or diseased sample, and determining whether the sample of the subjecthas the disease or condition. Examples of non-cancer related diseases ordisorders include congential disorders of glycosylation, such as failureto thrive, mental retardation, hypotonia, hypoglycemia, cerebellarhypoplasia, liver dysfunction, coagulopathy, partial TBG deficiency,perinatal dysmorphia, microcephaly, loose wrinkled skin, skeletalanomalies, short stature, recurrent infections, thrombocytopenia,neutropenia, seizures and stroke-like episodes, and dandy-walkermalformation.

In accordance with the inventive methods, the terms “cancers” or“tumors” also include but are not limited to adrenal gland cancer,biliary tract cancer; bladder cancer, brain cancer; breast cancer;cervical cancer; choriocarcinoma; colon cancer; endometrial cancer;esophageal cancer; extrahepatic bile duct cancer; gastric cancer; headand neck cancer; intraepithelial neoplasms; kidney cancer; leukemia;lymphomas; liver cancer; lung cancer (e.g. small cell and non-smallcell); melanoma; multiple myeloma; neuroblastomas; oral cancer; ovariancancer; pancreas cancer; prostate cancer; rectal cancer; sarcomas; skincancer; small intestine cancer; testicular cancer; thyroid cancer;uterine cancer; urethral cancer and renal cancer, as well as othercarcinomas and sarcomas.

Although specific terms are employed herein, they are used in a genericand descriptive sense only and not for purposes of limitation. Unlessotherwise defined, all technical and scientific terms used herein havethe same meaning as commonly understood by one of ordinary skill in theart to which this presently described subject matter belongs.

Throughout this specification and the claims, the terms “comprise,”“comprises,” and “comprising” are used in a non-exclusive sense, exceptwhere the context requires otherwise. Likewise, the term “include” andits grammatical variants are intended to be non-limiting, such thatrecitation of items in a list is not to the exclusion of other likeitems that can be substituted or added to the listed items.

For the purposes of this specification and appended claims, unlessotherwise indicated, all numbers expressing amounts, sizes, dimensions,proportions, shapes, formulations, parameters, percentages, parameters,quantities, characteristics, and other numerical values used in thespecification and claims, are to be understood as being modified in allinstances by the term “about” even though the term “about” may notexpressly appear with the value, amount or range. Accordingly, unlessindicated to the contrary, the numerical parameters set forth in thefollowing specification and attached claims are not and need not beexact, but may be approximate and/or larger or smaller as desired,reflecting tolerances, conversion factors, rounding off, measurementerror and the like, and other factors known to those of skill in the artdepending on the desired properties sought to be obtained by thepresently disclosed subject matter. For example, the term “about,” whenreferring to a value can be meant to encompass variations of, in someembodiments, ±100% in some embodiments ±50%, in some embodiments ±20%,in some embodiments ±10%, in some embodiments ±5%, in some embodiments±1%, in some embodiments ±0.5%, and in some embodiments ±0.1% from thespecified amount, as such variations are appropriate to perform thedisclosed methods or employ the disclosed compositions.

Further, the term “about” when used in connection with one or morenumbers or numerical ranges, should be understood to refer to all suchnumbers, including all numbers in a range and modifies that range byextending the boundaries above and below the numerical values set forth.The recitation of numerical ranges by endpoints includes all numbers,e.g., whole integers, including fractions thereof, subsumed within thatrange (for example, the recitation of 1 to 5 includes 1, 2, 3, 4, and 5,as well as fractions thereof, e.g., 1.5, 2.25, 3.75, 4.1, and the like)and any range within that range.

EXAMPLES

The following Examples have been included to provide guidance to one ofordinary skill in the art for practicing representative embodiments ofthe presently disclosed subject matter. In light of the presentdisclosure and the general level of skill in the art, those of skill canappreciate that the following Examples are intended to be exemplary onlyand that numerous changes, modifications, and alterations can beemployed without departing from the scope of the presently disclosedsubject matter. The synthetic descriptions and specific examples thatfollow are only intended for the purposes of illustration, and are notto be construed as limiting in any manner to make compounds of thedisclosure by other methods.

Example 1

Mass spectrometry imaging of glycans from tissue section. FIG. 3 shows arepresentative schematic of an imaging platform using the inventivemethods. A FFPE tissue section is rehydrated, the proteins in the tissuesection are denatured, and microarray printing using the release agentPNGase F is allowed to occur. PNGase F is the enzyme that cleavesN-linked glycans from their host proteins. To preserve the spatialdistribution of the glycans, a microarray printer can be used to applythe PNGase F on the tissue in a grid. Then, a matrix, such as2,5-dihydroxybenzoic acid (DHB), can be sprayed over the tissue using anairbrush. The tissue can then be analyzed with a mass spectrometer(Axima Resonance MALDI QIT-TOF, Shimadzu). One difference between aconventional MALDI analysis and the methods of the present invention isthat the tissue is raster scanned by the laser in the x and y directionsand mass spectra are acquired for each pixel on the tissue. At thispoint, by mapping the intensity of various peaks as a function oflocation, ion images can be generated for each glycan structure detectedin the mass spectra.

The methods of the present invention were used to analyze mouse braincoronal sections (FIG. 4). On the left of FIG. 4, the tissue stainedwith AAL lectin is depicted, and the cerebral cortex and brain stemregions are marked. The AAL lectin binds to the fucosylated glycans.According to this image, although fucosylated glycans are distributedthroughout the brain, they seem to be higher in abundance in thecerebral cortex compared to the midbrain in the brain stem. The middlepanels shows the MALDI images for two glycan ions that are overlaid andthe structures of the glycan ions are shown below the image. The redsignal corresponds to a glycan, which is highly fucosylated and thegreen signal shows the distribution of glycans with only one fructose.On the right of FIG. 4, the ion images are shown for those same glycansfor a tissue that is not treated with PNGase F. Therefore, the enzymaticdeglycosylation results in releasing of glycans and their subsequentdesorption and ionization with MALDI-MS.

FIG. 5 depicts ion images of some of the detected fucosylated glycansand these are compared with AAL lectin staining of an adjacent tissuesection. Based on the AAL staining, fucosylation occurs in the cerebrumas well as brain stem, with a relatively higher abundance in thecerebral cortex. The ion images acquired from fucosylated glycan alsoshow a similar pattern. With the exception of a glycan of 2053 Da, otherglycans are either uniformly distributed over the tissue or have higherabundance in the cerebral cortex.

FIG. 6 shows the mass spectrum of the tissue section averaged over alltissue pixels. The identified glycans were compared with the functionalglycomics database. Based on this comparison, approximately 72% of themouse brain non-sialylated N-linked glycans were able to be detected. Inthis experiment, however, sialylated glycans were missing in thisspectrum. Without wishing to be bound to any one particular theory, themissing sialylated glycans may be due to the loss of sialic acid duringsample preparation or mass spectrometry analysis.

In accordance with some embodiments, the methods of the presentinvention were extended to image sialylated glycans from FFPE tissues aswell (FIG. 7). Sialic acid is a terminal sugar residue on N-linkedglycans shown by a diamond in glycan schematics. This sugar has provento be challenging to analyze because it easily gets cut off from theglycans due to harsh sample preparation conditions or during post sourcedecay MALDI-MS analysis. A technique for stabilizing the sialic acidresidues in MALDI analysis by labeling them with p-toluidine wasdeveloped. Using these inventive methods, the labeled glycans, alongwith the non-sialylated glycans, are released from glycoprotein byenzymatic deglycosylation and analyzed with mass spectrometry.

The new sialic acid protection methods of the present invention weretested on FFPE prostate tissue sections (FIG. 8). The mass spectrum onthe upper panel shows the mass spectral peaks corresponding tosialylated glycans after in situ labeling with p-toluidine. By comparingthese results with the control group, where no p-toluidine was applied,it was shown that this technique significantly improves the signal tonoise ratio and detection of sialylated glycans.

FIG. 9 shows ion images of four sialylated glycans along with theirstructures. The histostaining with SNA lectin, which is used to stainsialylated glycans, showed a quite weak signal from sialylated glycanson tissue. Referring once again to FIG. 9, the sialylated glycans, eventhough they are low in abundance, were mostly located in the threeregions marked by black arrows. Despite the low abundance of sialylatedglycans and their weak staining in lectin histostaining images, themass-spectrometry based detection was able to detect at least foursialylated glycans (FIG. 9).

The methods of the present invention provides release agent printingcombined with MALDI mass spectrometry imaging to directly profile andimage N-linked glycans from FFPE tissue sections (FIG. 10). In addition,in situ labeling of sialylated tissue glycans with p-toluidine wasperformed to image them on FFPE tissue sections.

Example 2

Concentration Dependent Sensitivity and SD. Sensitivity and standarddeviation (SD) of an analyte greatly depend on the concentration of thetarget analyte in the sample. To illustrate the dependence, wecalculated the sensitivity and SD versus analyte concentration usingAngiotensin II as an example and the results are shown in (FIG. 13). Thecalibration curve of Angiotensin II was generated by analyzingsequential dilutions of this peptide with the mass spectrometer. Thesensitivity was calculated from the calibration curve by dividing thesignal difference by the concentration difference for two adjacent datapoints at each concentration. The standard deviation was computed fromten normalized mass spectral signals and is denoted as SD. Due to thesigmoidal shape of the calibration curve (FIG. 11 and FIG. 13A), thesensitivity, i.e. the slope of this curve stays stable at its maximumvalue over the linear range of the assay, and decreases as theconcentration falls below the LOD or above the upper linear range (FIG.11 and FIG. 13B). The standard deviations are usually modest at loweranalyte concentration and increase with analyte concentration (FIG.13C). Moreover, the coefficient of variation (CV) defined by thestandard deviation divided by the signal mean also associated with theconcentration of the target analyte and drops rapidly as theconcentration of the analyte increases (FIG. 13D). As a result, thereare certain concentrations of analyte with a lower SD to sensitivityratio than this ratio at the background. These concentrations generallylie near the LOD of the target analyte, where the sensitivity increasesdramatically (FIG. 11, FIGS. 13A and 13B), but SD still remainsrelatively low (FIG. 13C). Considering that the LOD depends on the ratioof SD to sensitivity, the LOD can then be improved by shifting thereference point of concentration to this range of a higher slope on thecalibration curve by spiking additional analytes into the sample.

Example 3

Determining LODs of Target Analytes in Simple Mixture. To determinewhether the LOD could be lower with the target analytes spiked in TADsolution, we analyzed the target peptides in different dilutions incontrol solution (which did not have any spiking target peptides added)and in various TAD solutions (which had a different amount of targetpeptides spiked in the solution). The mass spectral peaks of AngiotensinI is depicted in FIG. 14 for the control and the TAD solution group. Forthis peptide, the measured LOD_(orig) was 64.5 fmol/μL. Therefore, themass spectral peak of Angiotensin I (m_(a)=1296.685), averaged over theten measurements, is not distinguishable from the background atconcentration of 31.25 fmol/μL (FIG. 14A). By spiking the target analytewith a concentration C=50 fmol/μL, the spectral signal is boosted andthe LOD reduces to 22.5 fmol/μL. Consequently, as shown in FIG. 14B, theaveraged mass spectral peak of Angiotensin I at the endogenousconcentration of 31.25 fmol/μL and exogenous concentration of 50 fmol/μL(X=31.25 and C=50 fmol/μL, i.e. 81.25 fmol/μL) is significantly higherthan the background at exogenous concentration of 50 fmol/μL.

To determine whether this LOD improvement method and the dependence ofthe LOD improvement on the spiking target analyte concentration could beapplicable to other analytes, three analytes, Angiotensin I, AngiotensinII, and β-Amyloid (1-15), with three different concentrations of targetanalytes spiked in TAD solution were tested. Nine experimentalconditions (three exogenous concentrations for each of the threetargeted peptides) were studied in four replicate measurements withindependent sample preparation. The experiment was performed in bothCHCA and DHB as the MALDI matrix. On average, in CHCA matrix, TADsuccessfully improved the LODs in all nine experimental conditions (FIG.15A). TAD successfully improved the LODs in eight of nine experimentalconditions when using DHB as matrix (FIG. 15B). Improvement factor isdefined by LOD_(orig) divided by LOD_(C), where LOD_(orig) is the LOD ofthe control group with no exogenous peptides spiked to the solution, andLOD_(C) represents the LOD that was achieved by boosting theconcentration by spiking the analyte of a concentration C fmol/μL.

Additionally, we estimated the LOD improvement expected at eachexogenous concentration using the MALDI-MS calibration curve for eachpeptide. The experimental LOD_(orig) was calculated using eq 1 and thepredicted LOD_(C) was estimated using eq 2 where the LOD_(orig) andLOD_(C) are graphically depicted in FIG. 11. For all three peptides, thepredicted improvement factor is very close to 1 at the lower end of thetarget analyte spiking concentrations, but it has local maxima at themidranges and decreased at higher spiking concentration. For example,the predicted LOD_(C) for Angiotensin II using CHCA and DHB matrices inthe simple background experiment is plotted as a function of spikingconcentration C divided by LOD_(orig) (FIG. 16). Maximum predicted LODimprovement was achieved when the spiking peptide concentration is closeto LOD_(orig). For all three peptides, there is a local maximum on theestimated LOD curve (corresponding to an optimal LOD improvement) at aspiking concentration of the target analyte around the controlLOD_(orig). The optimal spiking concentration and the correspondingestimated LOD improvement factor for the three peptides are listed inTable 1. This quantitative method suggests that maximum improvement ofthe detection limit for low abundance analytes depends not only on theanalyte but also on the MALDI matrix, which affect the signal to noiseratio of each analyte. Maximal improvement factor for the analyte ofinterest can be reached by spiking the target analyte at a concentrationclose to LOD_(orig) into the unknown sample for the analysis of targetanalytes.

TABLE 1 The optimal exogenous concentrations and improvement factors forsimple background experiment averaged over four replicates. The optimalexogenous concentration is close to LOD_(orig). On average, the optimalexogenous concentration is 1.26 LOD_(orig) over all three peptides inCHCA matrix, which is lower than the optimal exogenous concentration of1.58 LOD_(orig) for DHB matrix. Additionally, CHCA yields a higherpredicted optimal improvement factor compared to DHB matrix. Localmaximum exogenous Local maximum concentrations improvement factorsPeptide Matrix (C/LOD_(orig)) (LOD_(orig)/LOD_(C)) Angiotensin I CHCA0.72 ± 0.09 3.80 ± 0.68 DHB 1.75 ± 0.62 2.58 ± 0.92 Angiotensin CHCA0.85 ± 0.21 3.93 ± 1.41 II DHB 1.83 ± 0.18 1.63 ± 0.22 β-Amyloid CHCA2.21 ± 0.82 1.82 ± 0.31 (1-15) DHB 1.17 ± 0.30 4.04 ± 1.28 All threeCHCA 1.26 ± 0.47 3.18 ± 0.68 peptides DHB 1.58 ± 0.21 2.75 ± 0.70

Example 4

Determining LODs of Target Analytes in Complex Mixture. To determinewhether the LOD improvement observed with a solution of a single analyteusing the TAD method could apply to target analytes in a complexmixture, the above three target analytes were analyzed in the mixture ofserum peptides. Five spiking concentrations of each target peptide wereconsidered and the triplicate experiments were performed for each case.Of the fifteen experimental conditions (five exogenous concentrationsfor each of the three target peptides), the average LOD of triplicateexperiments was improved in ten targeted peptide-exogenous peptide pairscompared to the corresponding control (FIG. 17). In general, highestspiking concentrations of target peptides result in low improvementfactors, and in some cases fail to achieve any improvements. Theestimated LOD curve for Angiotensin II in complex mixture shows similarpattern to the simple background experiment (FIG. 18), with a localmaximum at exogenous concentration of LOD_(orig). The optimal exogenousconcentrations and the achieved improvement factors for complexbackground experiment are shown in Table 2. The optimal predictedexogenous concentrations are estimated to be close to 2 LOD_(orig),which is slightly higher than that of the simple background experiment.Also, the predicted maximum LOD improvement factor in the complexbackground experiment is lower than that of the simple backgroundexperiment for the same three examined peptides.

TABLE 2 The optimal exogenous concentrations and improvement factors forcomplex background experiment using CHCA matrix averaged over triplicateindependent experiments. On average, the optimal exogenous concentrationrequired for predicted maximum LOD improvement factor is close to 2LOD_(orig). Local maximum Local maximum exogenous improvement factorsPeptide concentrations (C/LOD_(orig)) (LOD_(orig)/LOD_(C)) Angiotensin I2.57 ± 0.31 3.05 ± 0.81 Angiotensin II 0.71 ± 0.31 1.85 ± 0.85 β-Amyloid(1- 3.15 ± 2.59 1.59 ± 0.48 15) All three 2.14 ± 0.74 2.16 ± 0.45peptides

TAD takes advantage of the carrier effect of standard additions toreveal the signal that is buried in noise due to complexity of thesample. The carrier effect is a repeatedly reported phenomenon, which tothe best of our knowledge has not previously been used in quantitativemass spectrometry as a technique for improving the detection. TADprovides a 3-fold LOD improvement in simple background, and a 2-fold LODimprovement in complex background experiments. This enhancement achievedthrough TAD might be modest compared to signal enrichment techniquessuch as chromatography, fractionation, or affinity enrichment; however,TAD can be applied in combination with these techniques to furtherimprove the detection limit by 2- to 3-fold. Also, further improvementof detection limit using TAD technique can be achieved by highlycontrolled conditions with high reproducibility. Therefore, thefunctionality of TAD might improve in a more controlled and reproducibleexperimental setting such as automated clinical assays and in targeteddetection of glycans and proteins in situ by mass spectrometry asdisclosed herein.

The presently disclosed methods include direct profiling of glycans ontissues, in situ chemical labeling and/or enzymatic modifications ofglycans and glycoproteins on tissue slides, quantitative analysis oftissue glycans and glycoproteins using isotopic labeling, and targeteddetection of glycans and proteins in situ by mass spectrometry.

All references, including publications, patent applications, andpatents, cited herein are hereby incorporated by reference to the sameextent as if each reference were individually and specifically indicatedto be incorporated by reference and were set forth in its entiretyherein.

The use of the terms “a” and “an” and “the” and similar referents in thecontext of describing the invention (especially in the context of thefollowing claims) are to be construed to cover both the singular and theplural, unless otherwise indicated herein or clearly contradicted bycontext. The terms “comprising,” “having,” “including,” and “containing”are to be construed as open-ended terms (i.e., meaning “including, butnot limited to,”) unless otherwise noted. Recitation of ranges of valuesherein are merely intended to serve as a shorthand method of referringindividually to each separate value falling within the range, unlessotherwise indicated herein, and each separate value is incorporated intothe specification as if it were individually recited herein. All methodsdescribed herein can be performed in any suitable order unless otherwiseindicated herein or otherwise clearly contradicted by context. The useof any and all examples, or exemplary language (e.g., “such as”)provided herein, is intended merely to better illuminate the inventionand does not pose a limitation on the scope of the invention unlessotherwise claimed. No language in the specification should be construedas indicating any non-claimed element as essential to the practice ofthe invention.

Preferred embodiments of this invention are described herein, includingthe best mode known to the inventors for carrying out the invention.Variations of those preferred embodiments may become apparent to thoseof ordinary skill in the art upon reading the foregoing description. Theinventors expect skilled artisans to employ such variations asappropriate, and the inventors intend for the invention to be practicedotherwise than as specifically described herein. Accordingly, thisinvention includes all modifications and equivalents of the subjectmatter recited in the claims appended hereto as permitted by applicablelaw. Moreover, any combination of the above-described elements in allpossible variations thereof is encompassed by the invention unlessotherwise indicated herein or otherwise clearly contradicted by context.

The invention claimed is:
 1. A method for direct mass spectrometryimaging of glycans in a biological sample where spatial distribution ofthe glycans in the sample is maintained, the method comprising: (a)obtaining a biological sample comprising a tissue section having atleast one glycoprotein on a solid support; (b) denaturing the at leastone glycoprotein in the biological sample of (a); (c) applying at leastone releasing agent onto the biological sample of (b) to release the atleast one glycan from the at least one glycoprotein in the biologicalsample of (b); (d) performing raster analysis of the biological sampleof (c) with a mass spectrometer in an X and Y direction and acquiringthe mass spectra for each pixel located on the tissue and identifyingthe at least one glycan at each pixel.
 2. The method of claim 1, whereinthe biological sample comprises a paraffin-embedded tissue.
 3. Themethod of claim 1, wherein the biological sample comprises aformalin-fixed tissue.
 4. The method of claim 2, wherein the biologicalsample is rehydrated prior to step (b).
 5. The method of claim 3,wherein the biological sample is rehydrated prior to step (b).
 6. Themethod of claim 1, wherein the at least one releasing agent is appliedto the onto the biological sample of (b) with a microprinter.
 7. Themethod of claim 1, wherein releasing the at least one glycan occurs byusing an enzyme selected from the group consisting of Endoglycosidase H(Endo H), Endoglycosidase F (EndoF), and N-Glycanase F (PNGaseF).
 8. Themethod of claim 7, wherein releasing the at least one glycan occurs byusing the enzyme PNGaseF.
 9. The method of claim 1, further comprisingafter step (d) coating the biological sample with a matrix.
 10. Themethod of claim 9, wherein the matrix comprises 2,5-dihydroxybenzoicacid (DHB).
 11. The method of claim 1, wherein the mass spectrometry isMALDI-mass spectrometry.
 12. The method of claim 11, wherein theMALDI-mass spectrometry comprises MALDI time-of-flight (TOF) massspectrometry.
 13. The method of claim 11, wherein the MALDI-massspectrometry comprises MALDI-quadrupole ion trap (QIT)-TOF massspectrometry.
 14. The method of claim 1, the method further comprising:b1) adding to the sample a known concentration of at least oneglycoprotein; d1) calculating the endogenous amount of the at least oneglycan in the sample wherein the endogenous amount of the at least oneglycan in the sample=the total amount of the at least one glycan in thesample the amount of the at least one glycan added in b1).